Improving Passenger Experience and Trust in Automated Vehicles Through User-Adaptive HMIs

“The More the Better” Does Not Apply to Everyone

Bibliographic Data

ID13136703
AuthorsFranziska Hartwich (Chemnitz University of Technology, corresponding author), Cornelia Hollander (0000-0002-5522-0209, Chemnitz University of Technology), Daniela Johannmeyer (Oldenburger Institut für Informatik), Josef F Krems (0000-0001-6156-9944, Chemnitz University of Technology)
Year2021
Volume3
Publication date2021-06-28
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Human Dynamics (JOURNAL)
Journal identifiersISSN: 2673-2726 • E-ISSN: 2673-2726
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fhumd.2021.669030
OpenAlexW3177369277
LanguageEN
Citations received1
References cited30

Automated vehicles promise transformational benefits for future mobility systems, but only if they will be used regularly. However, due to the associated loss of control and fundamental change of in-vehicle user experience (shifting from active driver to passive passenger experience), many humans have reservations toward driving automation, which question their sufficient usage and market penetration. These reservations vary based on individual characteristics such as initial attitudes. User-adaptive in-vehicle Human-Machine Interfaces (HMIs) meeting varying user requirements may represent an important component of higher-level automated vehicles providing a pleasant and trustworthy passenger experience despite these barriers. In a driving simulator study, we evaluated the effects of two HMI versions (with permanent vs. context-adaptive information availability) on the passenger experience (perceived safety, understanding of driving behavior, driving comfort, driving enjoyment) and trust in automated vehicles of 50 first-time users with varying initial trust (lower vs. higher trust group). Additionally, we compared the user experience of both HMIs. Presenting driving-related information via HMI during driving improved all assessed aspects of passenger experience and trust. The higher trust group experienced automated driving as safest, most understandable and most comfortable with the context-adaptive HMI, while the lower trust group tended to experience the highest safety, understanding and comfort with the permanent HMI. Both HMIs received positive user experience ratings. The context-adaptive HMI received generally more positive ratings, even though this preference was more pronounced for the higher trust group. The results demonstrate the potential of increasing the system transparency of higher-level automated vehicles through HMIs to enhance users’ passenger experience and trust. They also consolidate previous findings on varying user requirements based on individual characteristics. User group-specific HMI effects on passenger experience support the relevance of user-adaptive HMI concepts addressing varying needs of different users by customizing HMI features, such as information availability. Consequently, providing full information permanently cannot be recommended as a universal standard for HMIs in automated vehicles. These insights represent next steps toward a pleasant and trustworthy passenger experience in higher-level automated vehicles for everyone, and support their market acceptance and thus the realization of their expected benefits for future mobility and society

Automation · Computer security · Context (archaeology · Driving simulator · Human–computer interaction · Simulation · Trustworthiness · User experience design · Autonomous Vehicle Technology and Safety · Computer Science · Engineering · Human-Automation Interaction and Safety · Traffic and Road Safety

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